Change log
Release-to-release tracker diff with separate policy-text, newly-extracted claim, evidence, and source snapshot categories.
Current public record freshness and review state.
Imperial College London currently has 10 source-backed claim records and 14 official source attributions. Latest tracked changed date: May 6, 2026. No tracker diff rows are recorded in the latest public release.
This tracker is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.
Newly extracted claims are tracker additions and are not necessarily newly published by the university. Source snapshot changes show hash changes for the same source URL and are not by themselves policy changes.
Semantic classification for this release diff.
Unified tracker diff generated from the previous and current public release snapshots.
No tracker claim/evidence/source changes are recorded for this university in the latest public release.
10 claim records
Students should include a statement acknowledging their use of generative AI tools for all assessed work, specifying the tool name and version, publisher, URL, a brief description of how it was used, and confirmation that the work is their own. Further requirements such as prompts used, date of output, the output obtained, and how it was modified may also be required by individual departments.
Users of Imperial's dAIsy platform must not upload third-party content they are not permitted to share. Reuse of AI outputs must comply with licensing and academic citation norms. When communicating externally, dAIsy outputs must not be presented as Imperial's position without approval.
Imperial College London has established five Generative AI Principles (aligned with Imperial Values: Respect, Collaboration, Excellence, Integrity, Innovation) to provide a foundational framework for approaches to using generative AI in teaching, learning and assessment university-wide. The principles cover promoting critical use of AI, adopting a consistent ethical approach, and building a proactive research community around AI in education.
Unless explicitly authorised, using generative AI to create assessed work may be treated as an academic offence such as contract cheating under Imperial's Plagiarism, Academic Integrity & Exam Offences regulations. Improper use of AI can be investigated under the University's Academic Misconduct procedures.
Individual departments at Imperial may allow or prohibit the use of generative AI for specific assessments. Local (team/department/faculty) instructions take precedence over university-wide guidance. Students should check their department's current policy on using and disclosing generative AI in academic work and follow their module leader's instructions.
Imperial's dAIsy AI platform uses University SSO authentication with auditing. Prompts and metadata are logged for operational monitoring, and AI model providers are configured not to train on user data. Users' prompts and responses are not used to train external AI models. dAIsy is approved for use with unrestricted data within Imperial's secure infrastructure.
Breaches of Imperial's dAIsy Use Policy may lead to action under Academic Misconduct procedures for students and HR/disciplinary processes for staff, as well as under Information Security and Data Protection policies. Sanctions may include removal of access, grade penalties, or formal disciplinary measures.
Research at Imperial that involves people, personal data, or sensitive topics may require ethics approval, a Data Protection Impact Assessment (DPIA), and data-governance controls before using any AI tool. Researchers must verify whether their use of AI in research requires special approval, particularly when uploading private or confidential research data.
All Imperial staff and students have access to Microsoft Copilot with Commercial Data Protection when signed in using their Imperial credentials. Microsoft Copilot has no access to organizational data in the Microsoft 365 Graph. Chat results are not saved or made available to Microsoft, and data does not pass outside the organisation.
Users of Imperial's dAIsy AI platform must always apply critical judgment to AI outputs. Generative AI can produce inaccurate or biased outputs ('hallucinate'), omit context, or reflect training-data biases. Users remain accountable for the accuracy, legality, and appropriateness of any content they submit or share through the platform.
14 source attributions
official_policy_page Tracker checked at May 6, 2026, 1:00 AM
official_guidance Tracker checked at May 6, 2026, 1:00 AM
other Tracker checked at May 6, 2026, 1:00 AM
other Tracker checked at May 6, 2026, 1:00 AM
official_guidance Tracker checked at May 6, 2026, 1:00 AM
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official_guidance Tracker checked at May 6, 2026, 1:00 AM
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official_policy_page Tracker checked at May 6, 2026, 1:00 AM
official_guidance Tracker checked at May 6, 2026, 1:00 AM
other Tracker checked at May 6, 2026, 1:00 AM
official_policy_page Tracker checked at May 6, 2026, 1:00 AM
official_guidance Tracker checked at May 6, 2026, 1:00 AM